A Cryptic Non-Inducible Prophage Confers Phage-Immunity on the Streptococcus thermophilus M17PTZA496

open9openda Silva Duarte, Vinícius; Giaretta, Sabrina; Campanaro, Stefano; Treu, Laura; Armani, Andrea; Tarrah, Armin; Oliveira de Paula, Sérgio; Giacomini, Alessio; Corich, Vivianada Silva Duarte, Vinícius; Giaretta, Sabrina; Campanaro, Stefano; Treu, Laura; Armani, Andrea; Tarrah, Armin; Oliveira de Paula, Sérgio; Giacomini, Alessio; Corich, Vivian

Sequential Symbolic Regression with Genetic Programming

This chapter describes the Sequential Symbolic Regression (SSR) method, a new strategy for function approximation in symbolic regression. The SSR method is inspired by the sequential covering strategy from machine learning, but instead of sequentially reducing the size of the problem being solved, it sequentially transforms the original problem into potentially simpler problems. This transformation is performed according to the semantic distances between the desired and obtained outputs and a geometric semantic operator. The rationale behind SSR is that, after generating a suboptimal function f via symbolic regression, the output errors can be approximated by another function in a subsequent iteration. The method was tested in eight polynomial functions, and compared with canonical genetic programming (GP) and geometric semantic genetic programming (SGP). Results showed that SSR significantly outperforms SGP and presents no statistical difference to GP. More importantly, they show the potential of the proposed strategy: an effective way of applying geometric semantic operators to combine different (partial) solutions, avoiding the exponential growth problem arising from the use of these operators

2021-2022 John Oliveira String Competition - Winner\u27s Recital

https://spiral.lynn.edu/conservatory_john-oliveira/1008/thumbnail.jp

2017-2018 John Oliveira String Competition - Final Round

https://spiral.lynn.edu/conservatory_john-oliveira/1005/thumbnail.jp

Comment on `Replica analysis of the p-spin interaction Ising spin-glass model'

We demonstrate that the analytic calculation of the 1RSB break point parameter in a paper by de Oliveira and Fontanari[1] is erroneous, due to the omission of a higher order term in a lengthy perturbative calculation, and provide a refinement of the accompanying numerical results. [1] V. M. de Oliveira and J. F. Fontanari, J. Phys. A 32, 2285 (1998)Comment: 4 pages, AMS LaTeX, 1 EPS figure; minor typo correcte

2018-2019 John Oliveira String Competition - Winner\u27s Recital

Winners Askar Salimdjanov, violin Feruza Dadabaeva, pianohttps://spiral.lynn.edu/conservatory_john-oliveira/1003/thumbnail.jp

2015-2016 John Oliveira String Competition - Winner\u27s Recital

Winners Yaroslava Poletaeva, violin Darren Matias, pianohttps://spiral.lynn.edu/conservatory_john-oliveira/1000/thumbnail.jp

2020-2021 John Oliveira String Competition - Semi-final and Final Rounds

Semi-finalists (Listed alphabetically) Kayla Bryan, violin Benjamin Kremer, violin Sebastian Orellana, violin Davron Ziyodjonov, cello Final Rounds Saturday, March 20, 2021 at 7:30 P.M. | Live-streamed from Amarnick-Goldstein Concert Hall Benjamin Kremer, violin Davron Ziyodjanov, cellohttps://spiral.lynn.edu/conservatory_john-oliveira/1006/thumbnail.jp